Publisher: 24
Sibanjan Das, Umit Mert Cakmak
AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible. In this book, you’ll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning. By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you’ll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions.
Faraz K. Kelhini, Butch Mayhew, Ben Fellows
Hands-On Automated Testing with Playwright draws from Faraz and Butch’s extensive experience to help you harness the full potential of Microsoft's Playwright framework.The book begins with a quick setup refresher, walking you through intermediate and advanced concepts such as dynamic content handling, accessibility testing, AI-generated test scripts, and parallel test execution. You'll explore real-world applications with end-to-end testing workflows for e-commerce and single-page applications. Alongside traditional topics such as accessibility, mobile, and visual regression testing, this book delves into modern trends such as CI/CD pipelines, DevOps integration, and AI-driven testing enhancements. Each chapter is packed with practical examples, expert techniques, and performance optimization tips, helping you gain a deep understanding of maintainable automation strategies. Whether you're transitioning from manual testing or expanding your automation toolbox, this Playwright book provides the skills and confidence to build future-proof testing systems in today's complex web development landscape.*Email sign-up and proof of purchase required
Rahul Shetty
Java is one of the most commonly-used software languages by programmers and developers. Are you from a non-technical background and looking to master Java for your automation needs? Then Hands-On Automation Testing with Java for Beginners is for you.This book provides you with efficient techniques to effectively handle Java-related automation projects. You will learn how to handle strings and their functions in Java. As you make your way through the book, you will get to grips with classes and objects, along with their uses. In the concluding chapters, you will learn about the importance of inheritance and exceptions with practical examples. By the end of this book, you will have gained comprehensive knowledge of Java.
Karl Gilbert Gupta, Benjamin Caudill
The cloud is taking over the IT industry. Any organization housing a large amount of data or a large infrastructure has started moving cloud-ward — and AWS rules the roost when it comes to cloud service providers, with its closest competitor having less than half of its market share. This highlights the importance of security on the cloud, especially on AWS. While a lot has been said (and written) about how cloud environments can be secured, performing external security assessments in the form of pentests on AWS is still seen as a dark art. This book aims to help pentesters as well as seasoned system administrators with a hands-on approach to pentesting the various cloud services provided by Amazon through AWS using Kali Linux. To make things easier for novice pentesters, the book focuses on building a practice lab and refining penetration testing with Kali Linux on the cloud. This is helpful not only for beginners but also for pentesters who want to set up a pentesting environment in their private cloud, using Kali Linux to perform a white-box assessment of their own cloud resources. Besides this, the book covers a large variety of AWS services that are often overlooked during a pentest — from serverless infrastructure to automated deployment pipelines. By the end of this book, you will be able to identify possible vulnerable areas efficiently and secure your AWS cloud environment.
Hands-On Azure Digital Twins. A practical guide to building distributed IoT solutions
Alexander Meijers
In today’s world, clients are using more and more IoT sensors to monitor their business processes and assets. Think about collecting information such as pressure in an engine, the temperature, or a light switch being turned on or off in a room. The data collected can be used to create smart solutions for predicting future trends, creating simulations, and drawing insights using visualizations. This makes it beneficial for organizations to make digital twins, which are digital replicas of the real environment, to support these smart solutions.This book will help you understand the concept of digital twins and how it can be implemented using an Azure service called Azure Digital Twins. Starting with the requirements and installation of the Azure Digital Twins service, the book will explain the definition language used for modeling digital twins. From there, you'll go through each step of building digital twins using Azure Digital Twins and learn about the different SDKs and APIs and how to use them with several Azure services. Finally, you'll learn how digital twins can be used in practice with the help of several real-world scenarios.By the end of this book, you'll be confident in building and designing digital twins and integrating them with various Azure services.
Kamil Mrzygłód
Microsoft Azure is one of the fastest growing public cloud service providers in the market currently, and also holds the second highest market share after AWS. Azure has a sophisticated set of services that will help you build fault-tolerant and scalable cloud-based applications.Hands-On Azure for Developers will take you on a journey through multiple PaaS services available in Azure, including App Services, Functions, and Service Fabric, and explain in detail how to build a complete and reliable system with ease. You will learn about how to maximize your skills when building cloud-based solutions leveraging different SQL/NoSQL databases, serverless and messaging components, and even search engines such as Azure Search. In the concluding chapters, this book covers more advanced scenarios such as scalability best practices, serving static content with Azure CDN, and distributing loads with Azure Traffic Manager.By the end of the book, you will be able to build modern applications on the Azure cloud using the most popular and promising technologies, which will help make your solutions reliable, stable, and efficient.
James Cross, Rudy Lai, Bartłomiej Potaczek
Apache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs.You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark.By the end of the book, you will be able to build big data analytical solutions using the various PySpark offerings and also optimize them effectively.
James Lee, Tao Wei, Suresh Kumar Mukhiya
Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements.To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets.By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently.